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Preprint (Author's original)arXiv.org - Non-exclusive license to distribute, Open
Preprint
Matching Consumer Fairness Objectives & Strategies for RecSys
arXiv (Cornell University)
07 Sep 2022
Abstract
The last several years have brought a growing body of work on ensuring that
recommender systems are in some sense consumer-fair -- that is, they provide
comparable quality of service, accuracy of representation, and other effects to
their users. However, there are many different strategies to make systems more
fair and a range of intervention points. In this position paper, we build on
ongoing work to highlight the need for researchers and practitioners to attend
to the details of their application, users, and the fairness objective they aim
to achieve, and adopt interventions that are appropriate to the situation. We
argue that consumer fairness should be a creative endeavor flowing from the
particularities of the specific problem to be solved.
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Details
- Title
- Matching Consumer Fairness Objectives & Strategies for RecSys
- Creators
- Michael D EkstrandMaria Soledad Pera
- Publication Details
- arXiv (Cornell University)
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Other Identifier
- 991021868725304721